{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 从零开始训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "import cv2\n",
    "import pickle\n",
    "from tqdm import tqdm\n",
    "import os\n",
    "import sys\n",
    "\n",
    "n_train = 12500\n",
    "path = 'D:\\\\PythonWorkSpace\\\\MLND\\\\P6_Dogs_VS_Cats\\\\train\\\\'\n",
    "height = 128\n",
    "width = 128"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 思路\n",
    "\n",
    "1.图像预处理\n",
    "\n",
    "    - 图像尺寸归一化（或补黑边）\n",
    "    - 图像尺寸压缩以减小数据量\n",
    "    - 取值归一化    \n",
    "    - 将训练数据Pickle为单个对象\n",
    "   \n",
    "   \n",
    "2.建立模型\n",
    "\n",
    "    - 从最简单的CNN模型入手，从0开始训练模型，看训练效果，不要幻想一次搞定。    \n",
    "    - 从预训练模型入手，进行迁移学习，对比自己训练模型看训练效果。\n",
    "\n",
    "\n",
    "3.增加功能：图像识别框\n",
    "\n",
    "    - FastRCNN    \n",
    "    - YOLO v2\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 数据预处理\n",
    "\n",
    "- 由于图片的尺寸相当随机，为方便给神经网络训练，需要先统一所有训练图片的尺寸。\n",
    "\n",
    "\n",
    "- 由于绝大多数图片的尺寸在 `500 x 500` 左右，如果用 `cv2.imread` 进行JPG解压缩并全部读入内存，总体积会从500M膨胀至17G，数据量较大。相比CIFAR10 `32 x 32` 的超迷你图片来说，会导致神经网络训练耗时长的多，因此应该对图片统一进行尺寸压缩。\n",
    "\n",
    "\n",
    "- 首先尝试将尺寸压缩至 `64 x 64`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████| 12500/12500 [00:26<00:00, 477.40it/s]\n",
      "100%|███████████████████████████████████████████████████| 12500/12500 [00:26<00:00, 465.95it/s]\n"
     ]
    }
   ],
   "source": [
    "img_db = np.zeros((25000, height, width, 3), dtype=np.uint8)\n",
    "\n",
    "for i in tqdm(range(n_train)):\n",
    "    img = cv2.imread(path + 'cat\\\\' + str(i) + '.jpg')\n",
    "    img = img[:, :, ::-1]\n",
    "    img = cv2.resize(img, (height, width))   \n",
    "    img_db[i] = img\n",
    "    \n",
    "for i in tqdm(range(n_train)):\n",
    "    img = cv2.imread(path + 'dog\\\\' + str(i) + '.jpg')\n",
    "    img = img[:, :, ::-1]\n",
    "    img = cv2.resize(img, (height, width))   \n",
    "    img_db[i + n_train] = img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25000, 128, 128, 3)"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_db.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1228800000"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_db.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1171.8751373291016 MB'"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(sys.getsizeof(img_db)/1024/1024) + ' MB'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from keras.utils import to_categorical\n",
    "zeros = np.zeros(12500, dtype=np.uint8)    # cat = 0\n",
    "ones = np.ones(12500, dtype=np.uint8)      # dog = 1\n",
    "labels = np.concatenate((zeros, ones))\n",
    "# labels = to_categorical(labels)\n",
    "obj = {'img_db': img_db, 'img_labels': labels}\n",
    "with open('training_set.p', 'wb') as file:\n",
    "    pickle.dump(obj, file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 导入预处理后的训练数据，方便随时开始训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25000, 128, 128, 3)"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open('training_set_128.p', 'rb') as f:\n",
    "    training_set = pickle.load(f)\n",
    "\n",
    "img_db = training_set['img_db']\n",
    "img_labels = training_set['img_labels']\n",
    "img_db.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 将训练集数据顺序随机化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "img_index = np.arange(25000)\n",
    "np.random.shuffle(img_index)\n",
    "img_db_shuffled = np.zeros((25000, height, width, 3), dtype=np.uint8)\n",
    "img_labels_shuffled = np.zeros((25000,), dtype=np.uint8)\n",
    "j = 0\n",
    "for i in img_index:\n",
    "    img_db_shuffled[j] = img_db[i]\n",
    "    img_labels_shuffled[j] = img_labels[i]\n",
    "    j += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lp6lJEO4zFUIrcYu4dNqEE1Nkqeid/Jyv7KWRZdlE6A9mHDJnryRNqVQqxlKQ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\ndnu6LZAtg+9b5PNDPC69IJ7na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      "text/plain": [
       "<matplotlib.figure.Figure at 0x19bda52fc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 检验一下打散图片和标签的关系是否正确\n",
    "img_id = np.random.choice(range(25000))\n",
    "plt.imshow(img_db_shuffled[img_id], cmap='gray')\n",
    "label = 'Cat'\n",
    "if img_labels_shuffled[img_id] == 1:\n",
    "    label = 'Dog'\n",
    "plt.title(label)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 划分训练集和验证集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2500, 128, 128, 3)\n",
      "(22500, 128, 128, 3)\n"
     ]
    }
   ],
   "source": [
    "x_test, y_test = img_db[:2500], img_labels[:2500]\n",
    "x_train, y_train = img_db[2500:], img_labels[2500:]\n",
    "print(x_test.shape)\n",
    "print(x_train.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from keras.models import Model\n",
    "from keras.layers import Input, Dense, Conv2D, Convolution2D, MaxPool2D, MaxPooling2D, Flatten, Dropout\n",
    "from keras.layers.normalization import BatchNormalization\n",
    "\n",
    "# CCM -> CCM -> CCM -> CCM -> Flatten -> Dropout -> FC -> output\n",
    "def create_model(num_CCM, num_kernel):\n",
    "    # Input Layers\n",
    "    input_tensor = Input((height, width, 3))\n",
    "    x = input_tensor\n",
    "\n",
    "    # Convolution + Pooling Layer (4层CCM级联，模拟VGG16的结构)\n",
    "    # 32C 32C M -> 64C 64C M -> 128C 128C M -> 256C 256C M\n",
    "    for i in range(num_CCM):\n",
    "        conv_num_output = num_kernel * (2**i)\n",
    "        x = Conv2D(filters=conv_num_output, kernel_size=3, strides=1, padding='valid', activation='relu')(x)\n",
    "        x = BatchNormalization()(x)\n",
    "        x = Conv2D(filters=conv_num_output, kernel_size=3, strides=1, padding='valid', activation='relu')(x)\n",
    "        x = BatchNormalization()(x)\n",
    "        x = MaxPool2D(pool_size=2, strides=2, padding='valid')(x)\n",
    "    \n",
    "    # Flatten\n",
    "    x = Flatten()(x)\n",
    "    \n",
    "    # Dropout\n",
    "    x = Dropout(0.25)(x)\n",
    "    \n",
    "    # Fully-Connected Layer\n",
    "    x = Dense(1, activation='sigmoid', kernel_initializer='he_normal')(x)\n",
    "\n",
    "    model = Model(inputs=input_tensor, outputs=x, name='dogVScat')\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 1. Create Model (3 CCM)\n",
    "model = create_model(3, 32)\n",
    "\n",
    "# 2. Compile Model with metrics/optimizer/loss\n",
    "model.compile(loss='binary_crossentropy',\n",
    "              optimizer='adadelta',\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_7 (InputLayer)         (None, 128, 128, 3)       0         \n",
      "_________________________________________________________________\n",
      "conv2d_33 (Conv2D)           (None, 126, 126, 32)      896       \n",
      "_________________________________________________________________\n",
      "batch_normalization_33 (Batc (None, 126, 126, 32)      128       \n",
      "_________________________________________________________________\n",
      "conv2d_34 (Conv2D)           (None, 124, 124, 32)      9248      \n",
      "_________________________________________________________________\n",
      "batch_normalization_34 (Batc (None, 124, 124, 32)      128       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_17 (MaxPooling (None, 62, 62, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_35 (Conv2D)           (None, 60, 60, 64)        18496     \n",
      "_________________________________________________________________\n",
      "batch_normalization_35 (Batc (None, 60, 60, 64)        256       \n",
      "_________________________________________________________________\n",
      "conv2d_36 (Conv2D)           (None, 58, 58, 64)        36928     \n",
      "_________________________________________________________________\n",
      "batch_normalization_36 (Batc (None, 58, 58, 64)        256       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_18 (MaxPooling (None, 29, 29, 64)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_37 (Conv2D)           (None, 27, 27, 128)       73856     \n",
      "_________________________________________________________________\n",
      "batch_normalization_37 (Batc (None, 27, 27, 128)       512       \n",
      "_________________________________________________________________\n",
      "conv2d_38 (Conv2D)           (None, 25, 25, 128)       147584    \n",
      "_________________________________________________________________\n",
      "batch_normalization_38 (Batc (None, 25, 25, 128)       512       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_19 (MaxPooling (None, 12, 12, 128)       0         \n",
      "_________________________________________________________________\n",
      "flatten_7 (Flatten)          (None, 18432)             0         \n",
      "_________________________________________________________________\n",
      "dropout_7 (Dropout)          (None, 18432)             0         \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 1)                 18433     \n",
      "=================================================================\n",
      "Total params: 307,233\n",
      "Trainable params: 306,337\n",
      "Non-trainable params: 896\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "model.fit(x=x_train, y=y_train, batch_size=128, epochs=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用验证集评估模型准确率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_pred = model.predict(x_test)\n",
    "y_result = []\n",
    "for i in y_pred:\n",
    "    if i[0] > 0.5:\n",
    "        y_result.append(1)\n",
    "    else:\n",
    "        y_result.append(0)\n",
    "y_result = np.array(y_result, dtype=np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8868"
      ]
     },
     "execution_count": 285,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = (y_result == y_test)\n",
    "np.count_nonzero(result)/2500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RNGIkLXqTkaWwgsFzeLDD3/vbP8tv3HiT1tdYY7AGjF+rzwKJOWqDUQFjEAGnghOHwWIx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kKtBBKcc9y7d4+rq0sxUXKdyYNRuIkWV07o8nrMhIpFzUarkWFk9G/tYZOmvoj9nEulFNFLJkCI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CsR5Ei5tpPY8K7FWPuxkr/v1yoKByI0MxuoGrZsN44m4aWozieQoxb5KzzVVZ9CboekpqnZJA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Dex5kIcJ9J60bYnOM0JrYX7+wPny5EvvjhCWXTziGM3veXlDDmrJaulRK2Gx2Pm8ptvuNvB\nd999y9v7ncYY1sjdZKhZqOUj0AijsH8Y+fj8hHEeMQFnNRrvJz/5Cb/7+hu+/v0fuMxH7h/2rDmx\nporUM5Ll5rHMDecaralQOa36NI6DZnJe5oQf3vDw9g3nufH4eOLbD7+iZs+b97/Au7fUDC/HF5xZ\nic7TmqE0Zdj5ISOlcTmdkar+zVQyNgaG3cSX77/g3ZsPfP3b3/PHbx5p1rLMiSE4WlHx7PmkToAq\nAJYwREp21wph2kWoK6agObf5whgOpLnx3R8/cTqunH7/GwZfeffmK4axUsmUPOOoSEvkbAgOQgAr\nFy6Xkw7Pq8GHkWWZ+f7777iULxmCxzVPPl2Ib3cYJ0hdaEUXTLUkwjRhTKHMs1Zf1VDM3D3FXsXG\nYjEuMCcljuzHgHM71pKxp+/YRcO0NxhJyNhV/aZ08J9l9RdyEZx49ruJ4K3CIUJE2oBzHuMWBUBg\nCMfKF+931AI+vqNW4WHc9RwPwzBN6pctDRu8zji7ZavWqgEyMXI63WgzIsLT0xMvJXI+H/tCYFUr\nmWns9xOHwwFjDHcMnE4XwhBZl4SPA8apxW1d12uwdSlqdyxVXRkqlF+vh2trldYMMQ7cH3bs/tJm\nbtIMlN014Li0QjX5ato11mD5AMBpiUAkuYQqZwA/Yc79SSDCJc8YZ0i1zz/siJEJ6W2YhETa6B/F\nAnvWAhC4PKsSP8Y7Lt2cLBKRrEPT5XTRuQWWVFTYWIolvWRqDVz+dMS3DU5pcE6lADHGm/tgdfz6\nn/6RYRgIIfD0dGSatqGswftPqpC3alpXTMzCNE2kdGa32+F9bwncxMkMLE8fGILAWvnw4nheHciB\nely7o2Pt//3Ky8sLw6AQw2EY+MXPH3g+ninN4IfEZS5kMzDLwrlcNFHYHHg6H7lkTykOTEDqTMkX\nxklBjKevO9l3HPiUhbu7SK2O549P/PSne8Ttcbt3PF4W0vHMaZl5c7fnec1M0fJ0fCG1PSLzFcXt\nSmVdL9cDelgbdZ6Jw8SIIQ73vH3znu8+PvOPv/q/WebM/Ztf4MJ7ljTiY6XU1uc4DkSDlO3dxFoy\nkxUstc9/PLV4Pj0V/uEfv8dPgS+//ILDfs93Hz9yPD3zH//nX/Ly8glrwVshuLV7Ql3f9OllqJF0\nDlOhVIuUSqmO5VT4h7/9J/7q5/+BL7/8t8zHhe//+HtKfc+/3z1A+USan0CgyID39zg7EsoLo1eP\n8Ho54Uzk7m6H8ws5V7yLyDhwXjwfP57ZdxeKj427SYheyP6J3aSi8v2+RxTi2EKdW2tYc1YoaGtA\nphxq99l2Heq7ASuep/M9ucGlWS4p4Wm8PYy8PWiSmPGGnMdOnxmuc7mcLDl7Qt1TqSzrWQkgzmO6\nrOfj9/DxY+OUFR3vJPDV/Xt+8dUdd/u/MCkI3Dhm/73Xn7c8cCN6bpaQ19kG2z9vtpDNeP/nxt/X\nXycGR4iRabdDLheqNHovt30TqgUytzR7EXNFxpTSCC4gotvYUhrGWNZVPYDLkrrHDs5rvuYv5Mty\n/d6udpV848XrzX0CYJrSdbAc7yopL9TzwjR4vn965ne//yPR9zASe3d9f6dpuj6VN0qG954PH87M\n86rhvGEEF7E+UKrh5VwYxsDjp8KaPhCDY1nP5HShlZVWMoe7HcMQ+PDd87XdCMHxxZfvaK3x9PTI\nN4/CYEfOqdKsYy3Caam8ebPjd7//RHozsJ5feD7N5KwV5eFw4P7+nsfHR0SkVwULhxHiYLl88wd2\n+zvMMBJ3hafTGYzl3eEtJhxYm0cWOM+FNM9E36UhEomANGFxBWShlYoPA7vDHak2jqcLprwwjiP7\nXeSyrLSoWa1iIrUVdvs963okzekqnQg9pb5UTVPzbegtG2Asy1z47tvvebj/a6a/HrmcE19//Qf2\noyP9ZIeVcmWoGdNIecb5xuUyszuoYHldF+IAJVdKnRVmOQw8ffA8vcw0E/nyizecL0eePn73/7Z3\nLj+SZFcZ/517b0RkZmVV9Ws8Nh4LD8gbCyGwkIUEQggJYQzCLL1AYsEfAGKBbFlCYgkLxBoBkiUe\n3oCEZbEx2BI7DMY2GjOMx2OP59Xv6uqqzIznvYfFuZGZ3dP2eNpjV1cpv1KooiIfdU9k5Ilzzz3n\n+yjZ4/DaIRJXNH1D0Ah9j8NTllYilQAVhbiiChVilDSEymoK2zHKL2d0Xcf+YcmqjZx0CmHOUNdM\n/MDBtMR7ITjQyur4fFCKwuVr1ohCgwtAoG46+phpv6qSopxyenWPe0d7LFNktYic3uuYTYTpxLE/\nP2cLCuZojMJm5I7aZujc7LN2SmMfJ2x4pcbHt53X6AzHnrft542/t3mn+i6SYkeKPEAxs81L5UQf\n6I0bhWNHjczRkZEj0ZF1RLG6fFOFys3Hg+JcwGVlKO88ZJ1IKabrPr2u6+iT/c/VYlg38tPdtMby\nmFg2juDEdFPLElUHOQcXY2SVHHXdIlLknIlVn5/evsskl1wkaehSbXmO4Gm7Ad8M3BtFm3MuCVWq\n4Ol74fUbJ4CSnAADPlhN0iu3ary38/vKrVepQiQmgXJG2yW6pLz08m1kaHiRHokdyR+uHXzf32Vv\nb28tiThyec0mkf39fbqh5/DyVWsN8iU+fw7Xj1fc75RwNzLbE9rmhGa1ZFoOpAROCvYvF0jsCH5A\nkkn+Xb48QUuo28T08JD793u+/Z1Xef311zg8LLl2ZZ8bt08YOlOO7ymNLbfZkB14r0yn1vKWUmKS\nv4viArP9GULJrDrgxvU7nB5/GXWO6WROisJyNVB6bCoZwLlEM6zwGCOvazorWo4DSXtit1rr+QY/\nZXk64aVvvMT80hV0MDWpF194jv6Zq1yaP4vnFGkaSufwXUtVTYjNCYpb38AltjiZrK879d50LoYe\niUIZ9igmoK3S1g2lFhzuz2HquX/nFq4X9qoZMpzig5Ak4nwixh7VhKQ+q8y3Rq8VWltwiEooZyQd\nqOaOS7M5d+qe06JnKp7jo3u88eotCi59337liXBuwJotYJtZYBsjo8C4YvPwFodc+PcQtc3I5BFj\nzF+6zftvP2d8bZGnj03XIk7Wha7b0ZvlAcjJT6GqJmte/74fSEkpywJNiaauodtww9k025Hyqbee\nO6Nuck4og7GoAvSxM5ZiEj0DPjOgJk2IExP7GJZI8lRFSdcODE5wMqEbhNgLhSQmkwnBGRFAnyXn\njHss17qFigZPNzT4IuCrTGgZe6R09KlmiJlnS4WD+SEOn3UtAqq5aLZUmnaFx1OvTF095ZXAvh8I\nXU9SB+2KblAm0z2Wy4G9yYxFXXMwv2zatcnYSIZBOb13uo4Gl4sG7z3Hpy3lSU/dtlS3TogpoU4p\nJxVD7HBxn6IMtPUps73Cosy+pyoqYlSclBwe3gEdKIPitCWlgaffveLStYbFqsaVM5J21G3DyaJF\n3T7z/UNeuX4Xokn8ndRKs+zWfP/DMFBVFXt7pWmZDgPzykhQQwi8W+Y0nVBWc+7fr1mc3KKopvnz\n8NSdUA+DEVyWHudhVXe4IjLUkbpvLEMgiq8Kur6z0okYKUqhqR137hwxm1+ma1uKwnP/+Ih7e8pi\ncYX9oiU1K0JZ4oimxtU36+vfruYeSSOdfo/LN8eQS0JSr2icQi+0i4brN29z9fIzaPK8/I1XeAO4\nfOUSz/5YoKwKVHvUJ4oyt7PFlqqsSP0SLyVBBkQi0VkuM8jUmHlUmATPzdM7dCvh5Pgmq2XDu546\nZzk3g2l6jtxRI8HjOBXdpuHejpo2VEQbGuPtqG2bE2qstt4m1dtmEAVISfF+Q3BojmzT9mHOifVr\nt9933Uyc94FMfRPXYxtfR14VGplt/Gi7GuWNPScx/rhAFjABnL2sG0ytCaDtY56am66rS86U1FOP\nV6NW6uuW0il93xDAbggpGXOTDrjSVk6HXHOnYiudSEJ8QcJuPlF7QmF9g7Fw+MxVthos1zmkDl84\nVKxIuu0be13K0SwO7231OSB0XSL40lZrGdvuok2TBAbdTM+NLNQTu4S4kqZPa4bZurUv+ySYuHIx\nndH2LRqDkWNm5g0P3L2/gDjkJvQB1ciQ7nDS5IR8VbGsV5nHLNAPyv3TGmRgkVlYZrMJsTOWkhAC\ndW0R79Wraa3Nce3QHK6qImEKBMpqShdrYt9Tt5EwGVBKjo6X9M0pRYhM1BNKz8mqB5doTluqqmU+\nnxMKoR8cQ5LNTSeaHmhVzliuGsQtWJzeR1zI13OkRe06CeBwnC6tiHh0ymV2eovFch1I9FkjY2RT\nsWlsQJMnDoGbN4549ic73n31aYbes1qc4lxJ91SF80oo7CJv2w7nt2Y8RNpulemy7P0nlaNrO4Kf\n0nctq1XKCnj37RwXmxnX94MnyLlt8PBUcTw2/t5+fDxWllY3sx31PczaOTrM7ehtm7LF2kVywSuW\nW0tbm/0v8FnE2CKXjaDxWthYt3mtxISTt6bXihrHNqzpxq3l3wgrHVZYKS4vMpj8NPrInGRhrUls\nJu9jY7go1mo25Eg2Wt+nMTCAaEJRGpen9ZIFahjv5OO5NKk5tx5/y6ARtDBnSAdiF2zSwRQfJK1F\nfUUVQehjgaSEiE2rJfUQKlSEiBDFmZ6l5E11ncjehtNJXmwyqT5xVvAMdgPpQ8I7v+6x7IeaIeV8\nmSpOIwMDKfZMek/Iq3R3799H7ixJTtnbn0Ob9W5JnKxqvvPKG/ggudUIptMJ9dJSEUZvb830N+5u\n+P9f9ks004m/frS0ftpiwrIdqFeNscm4gjuLltduHiGpxofIdDqhnE64fe+Eru+pxNhY9tuC2WxC\n3TeURWC1sin1dOo4WQWW7cCNl17HhQKNAwd7c6LuceeoowoKzEh+yqo38seub62Wrw8UxUAVAk1j\nfZzODWsnF4LZ1yEU3rPs4Og4cXScOFnC0Z1XuHVnxdWDQyaza/hyQL3jZLnCB1s5L5zHOaHuEkGs\nvi3p2EQPbROt/CklVnVL0yh3b91lsehYLmuuvesa6s5d5Cagm3m/lXIJMY2aBY9OIo4OzlpE7NhI\nbzxGeiMH2/Zixbb3H+tynHO5eLUjZocXEyYEwvrtsSrqtBmq5vHnyNP243rpfNsZP5A71NxgPHLT\nizk9YyU2qh2VIj95dBZvFqR16sczaKR+gIVbERHHoEqXm5yT5j7CMW/mLHdGbp9BAy69mfMeQH20\nXkas9tChqE/WapRFlwtnZKB2JzCmifXwBXDGGuIl68xKzE65sKS7c6jzW+dWUfdmhz70W+cuWZU/\n0efPsyTGDpGQN0FxOG9pAlVl0EQMVloyEIw5OSWSeERtgefeSUsxbHosk1p0k/CkrOK+7IUodiMa\nsjOLqqS6Xl+fq35ke07cf+2WTSH9BO9Kht7quE6OO27eex6vxoTT9Tb9liIQxTGZTaE+IoQTJmXF\ndFJycHDA/mxKzKUU0zJx0iyoe8dpY5X/ofC093oODgPD9YaT5YKDgwOqia3mLpcNTVOTdODSJcd8\nXnJpPuXoqF5T0oMFCWVpcpGqLfPyPoObEPYuMYSKf/nCFxmaBp9arj19QJhXrNQxrAZOT6PVCk6K\nNbW7c45ZyPRc3lr0RAIxJeq2oSw8fSro2oaTRUOUgmrvkDYKXTxnCwoPY0xmwrayz4Mye+OUdZvh\ndnztuozA+wdqdLzfovbe+gKPqj7jKt04nX3Ul3z8/9vbg4IbDl8Wa9UfEwORvFiSXw9IMhZYESvw\nlLzU4ERw+cvvMd0I1KiBYuoeMRpTfIccIWVyQ5NkcdR+iootHODzNFk2DLWqCqsat6ZJlzW7MCqI\njtOIHo83BfHBQS4h8Nj0VUTQVDAMmqMztdCRMcISUj4/Toc8zoSnx0myG5g40jAjxUgaqd4fdTHL\nEsabnhjBpMNWxDUKGlpiinS9rCl11lGk2Ep173MuVix/agpexnumwc6gzxEuPhCKGS4Upmfgpuub\nJkULyfjQnDfy0XqwGjejEfL0Q55+9w1VUZquakwIAYYIkwKSUPmKboj4MKVHqeuBLilFL8zwDKue\nIJHgOvyN5booWkQgJobQg1QkmdB3RsiZ+ha+dQuJLcfdwN7egpSMXbnPrCMpDUwmJxSlh0ylXxQF\nVVWtt5HS3TnHzN2iVc/88AqpgKN79+jrBXsl3F3dZlIH5uldvPbGTU5Pl7Rty5XLV9nLpAFt2+NX\nJ3Y+ZgWTSclkb8x1DxSlo+8jbWf8fItFR9O0VPOC67fvPfI7+Sg8Ic5NUUm2muIEl3QT42iyJts8\ndUpp4/yKoiAOSlVWTEpzSqEQUupxohRhwtANeASlQJzHB8f+fErXr+gbWw2VQfCupKKi1d6ai+NW\nxKC6npIJm6ppUIrSIS6ZHqVau4q4KQd7c9IQWS2WBHF0sTManuw7CgqGmGwKO1ZrC3j1EB1VCNQY\nWaX13gkFthI6Yp1/zM41jVGkA+esJGHqAi5HahalWt2g6qaboZHIcrlc3wz8Vv/eemKarD+iDB4V\npU8D0yKgQ48LWZkKofBCL5kIEqNQSpKT4DoxnrTxsnOg4sxpiimcB5eMU42BpIkyyDrnuUlDVJvV\nPDWtjajmTH0Al+z/qLgsINRhlRgul+0kpEl4PFESMIC3invNn7WooCOpoowLXVhReRKrvsfKGgD2\n9ow+6vT0FBG/7qwJaaASB4NQyT4aHZ0OVk5U9DgHJZu+0ZQiStb/1EiJ4vqaTgIxCm1KOGc3alWP\n9psFtNQGnFOcs8WwboiEInCnbXIeWOlOlvmS3hR3g+d02a2rCkAoSwf0xNjk6+beJrecFrkW9LYF\nATUMTclJ63n5Dbh7uuBbL9ccHR3TNFYmU1V3KMtjysqzqk9AAx5hUhWUoWBvWll3kBdUjhhSIrgD\n7h0rXWd5wa8//8r5ozx6HIwroOCYzWYczGdr5xZjnxO8D/Ktl2XJdFpxcDBnsTSpv67rcpvXRuX6\nrfBwOYnl8sYFBptOTidTNCb6tjPescfAtrgNsHaqD9fmfa9xjjV+3vt1Ddb4+jEH2Xb120rUgpVl\nVFVFzHTr4xcjpTsvO2wAAAQASURBVJQJBc3hPY7N4/tsR/Bv9z1GZz6mHR5s9xGG4c25vMfFGMV9\nt0j/ncT2Zz/OHB6u29z+fEeNUOccQ9M98D66ldMc/x71PsZUzuam6Db0R643uvimpSgKmtokFp1z\n3L59m+PjY1xqcyBifajHxy2qdtPywVasJdmN24ujDI6+77JzSwwpMa2urmsyx1nQ2znH8qP4QN5y\nECK3gSVw56zH8kPANS6mXXBxbdvZ9WTjx1X1qbd60hPh3ABE5L9U9efOehzvNC6qXXBxbdvZdTHw\nNngtd9hhhx3OD3bObYcddriQeJKc21+e9QB+SLiodsHFtW1n1wXAE5Nz22GHHXZ4J/EkRW477LDD\nDu8Yzty5ichHROQFEfmmiHzirMfzdiEifyMit0Tkua1jV0Tk8yLyYv59eeuxT2ZbXxCRXzubUb81\nROR9IvJFEflfEfm6iPx+Pn6ubRORiYh8SUS+lu36k3z8XNs1QkS8iHxFRD6X/74Qdj0WHkUf9KPa\nAA+8BPwEUAJfAz54lmN6DBt+CfgQ8NzWsT8DPpH3PwH8ad7/YLaxAp7NtvuztuG72PUe4EN5fx/4\nRh7/ubYNa7+d5/0C+A/g58+7XVv2/SHw98DnLsq1+LjbWUduHwa+qarfUtUO+AzwsTMe09uCqv47\ncPTQ4Y8Bn877nwZ+e+v4Z1S1VdVvA9/EzsETB1W9rqr/nfdPgeeB93LObVPDIv9Z5E0553YBiMgz\nwG8Af7V1+Nzb9bg4a+f2XuDVrb9fy8fOO55W1et5/wbwdN4/l/aKyPuBn8WinHNvW566fRW4BXxe\nVS+EXcBfAH/EyFlluAh2PRbO2rldeKjNAc7tkrSIzIF/BP5AVU+2HzuvtqlqVNWfAZ4BPiwiP/XQ\n4+fOLhH5TeCWqn75uz3nPNr1g+CsndvrwPu2/n4mHzvvuCki7wHIv2/l4+fKXhEpMMf2d6r6T/nw\nhbANQFWPgS8CH+H82/ULwG+JyMtYeudXRORvOf92PTbO2rn9J/ABEXlWRErg48Bnz3hM7wQ+C/xu\n3v9d4J+3jn9cRCoReRb4APClMxjfW0KMZuKvgedV9c+3HjrXtonIUyJyKe9PgV8F/o9zbpeqflJV\nn1HV92Pfoy+o6u9wzu36gXDWKxrAR7GVuJeAT531eB5j/P8AXAd6LG/xe8BV4N+AF4F/Ba5sPf9T\n2dYXgF8/6/F/D7t+EZvC/A/w1bx99LzbBvw08JVs13PAH+fj59quh2z8ZTarpRfGrre77ToUdthh\nhwuJs56W7rDDDjv8ULBzbjvssMOFxM657bDDDhcSO+e2ww47XEjsnNsOO+xwIbFzbjvssMOFxM65\n7bDDDhcSO+e2ww47XEj8P1CXNPDJ+LmLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x197027e1080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_path = 'D:\\\\PythonWorkSpace\\\\MLND\\\\P6_Dogs_VS_Cats\\\\test\\\\'\n",
    "random_img = np.random.choice(range(12500))\n",
    "img = cv2.imread(test_path + str(random_img) + '.jpg')\n",
    "img = img[:, :, ::-1]\n",
    "img_resize = cv2.resize(img, (128, 128))\n",
    "x = img_resize[None, :]\n",
    "y_pred = model.predict(x)\n",
    "y_pred = y_pred[0][0]\n",
    "result = ''\n",
    "prob = ''\n",
    "if (y_pred >= 0.5):\n",
    "    result = 'Dog'\n",
    "    prob = np.round(y_pred * 100, 2)\n",
    "else:\n",
    "    result = 'Cat'\n",
    "    prob = 100 - np.round(y_pred * 100, 2)\n",
    "    \n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.imshow(img, cmap='gray')\n",
    "plt.title(str(prob) + '% ' + result, size=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 输出预测结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████| 12500/12500 [01:02<00:00, 199.00it/s]\n"
     ]
    }
   ],
   "source": [
    "output = ['id,label',]\n",
    "test_path = 'D:\\\\PythonWorkSpace\\\\MLND\\\\P6_Dogs_VS_Cats\\\\test\\\\'\n",
    "for i in tqdm(range(1, 12501)):\n",
    "    img = cv2.imread(test_path + str(i) + '.jpg')\n",
    "    img = img[:, :, ::-1]\n",
    "    img_resize = cv2.resize(img, (128, 128))\n",
    "    x = img_resize[None, :]\n",
    "    y_pred = model.predict(x)\n",
    "    output.append(str(i) + ',' + str(y_pred[0][0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "with open('test.csv', 'w') as f:\n",
    "    for line in output:\n",
    "        f.writelines(line + '\\n')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
